Artificial intelligence is the new competitive advantage in sports
As football fans around the world tuned in on the 22ndn.d World Cup, they witnessed several uses of artificial intelligence. Video assistant technology helped referees on the field make accurate calls. More than 15,000 cameras tracked crowds in eight stadiums, and algorithms using data points such as ticket sales and stadium entrances predicted crowd patterns and helped prevent stampedes. Even the footballs are loaded with motion sensors, which report their location to a data center 500 times a second.
In fact, this year’s World Cup in Doha, Qatar was one of the highest-tech international sporting events to date. But we haven’t even seen all the ways AI will affect sports.
Consider using video replay to improve performance. The NBA’s Steph Curryand the NFL’s Tom Bradyare both fans of “film study,” going through plays and moves to figure out what to repeat and what to avoid. They are far from alone: Video replay is a common part of high-level training in many sports, including baseball, track, hockey and boxing.
But while new technology has revolutionized many aspects of elite sports—from radio headsets for coach-player communication to stronger, lighter equipment—the technology behind film studies hasn’t changed in a while. Yes, teams graduated from celluloid to digital files—but the task of organizing, editing, and learning from the film can be enormously labor-intensive, requiring someone to sift through hours of not-very-useful footage to find the plays they’re looking for. to. Sports organizations sometimes dedicate entire departments to this job.
A new generation of AI technologies promises to streamline this process considerably, giving the earliest adopters a competitive advantage. In fact, combining AI with film study could soon unlock a level of athletic performance that was unimaginable just a few years ago.
AI is already making a huge difference in how athletes train. Companies like Seattle Sports Sciences and California-based Sparta Science, for example, provide teams with machine learning tools that analyze athletes’ movements to improve form and even predict injuries.
The HomeCourt training app, which can be downloaded to a smartphone and used by individuals, harnesses the power of AI to allow basketball players to perfect their shooting form and track their progress. And apps like AIEndurance provide AI-based training for runners and cyclists.
Nevertheless, sports teams have only just begun to use AI for film studies, where the latest technologies will soon be able to provide far more insight in a fraction of the time. Recent advances in object recognition and tracking hold particular promise for gaining a competitive advantage.
The latest AI systems can recognize individual players, movements, games or patterns without a human needing to look at a screen. This means that a coach can find exactly the material he or she needs without searching through hours of video. For example, the Remark AI Box can connect to a team’s existing cameras to give them AI functionality without the need to install new sensors or other equipment.
Such breakthroughs have simplified the process of isolating the most relevant footage and compiling personalized video packages for each player on a team. While this task once required several full-time employees, with AI it can be done by a single person in minutes or even automated. It will certainly be a huge time saver for players and coaches.
The tried-and-true film study training technique was overdue for a technological upgrade. Now that teams are on the verge of incorporating AI in new ways, we can expect to see the results on the field of play.
Over time, AI-powered tools are bound to spread across different sports, leagues and levels of play. Athletes who ignore the opportunities are missing out on a huge opportunity.
Robbie Garvey is a former professional baseball player with stints in the Milwaukee Brewers, Los Angeles Dodgers and San Francisco Giants organizations. He has no interest in the companies mentioned in this text.
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